Mohamed Mydin Hj M.Abdul Kader
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Preferred name
Mohamed Mydin Hj M.Abdul Kader
Official Name
Mohamed Mydin , Hj M.Abdul Kader
Alternative Name
Kader, M. M.A.
Abdul Kader, M. Mohamed Mydin
Mohamed, M. M.A.K.
Abdul Kader, Mohamed Mydin M.
Kader, M. M.M.A.
Main Affiliation
Scopus Author ID
57202264868
Researcher ID
CYH-3060-2022

Research Output

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  • Publication
    Environmental lighting towards growth effect monitoring system of plant factory using ANN
    (Semarak Ilmu Publishing, 2025-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Muhammad Naufal Mansor
    ;
    Wan Azani Wan Mustafa
    ;
    Ahmad Anas Nagoor Gunny
    Malaysia is currently driven to become another most developed country in the world. Among other priority sector is Food Sustainability. Along the process, our vegetable supply-demand keeps increasing by year. Compared to traditional systems, closed systems or its other name called hydroponic is getting more important for plant production, with artificial light which has many potential advantages, including better quality transplants, shorter production time and less resource use. To gain full profit from it, the quality of vegetables needs to be controlled efficiently. Climate conditions, especially temperature and light intensity, have a significant impact on vegetable growth and yield, as well as nutritional quality. Plant growth and development are influenced by a variety of environmental factors, the most important one is light intensity. Among the problems to be tackled in this research are plant growth manual observation, light intensity variation and abundance of growth-related data to be evaluated manually. Therefore, to solve these problems, the specific type of vegetable used here is lettuce. The proposed methods are, observation of plant growth conducted automatically round the clock in intervals of 15 minutes for the whole month (estimated mature period of lettuce), using images captured. At the same time, the proposed light intensity which is red & white to the ratio of 2:1 (optimum ratio recommended by previous researchers) will be used. The issue of data to be evaluated manually will be solved using Artificial Neural Network (ANN) architecture, in specific Deep Learning. Concisely, the results & analysis shows the research is successfully developed for plant growth monitoring by using artificial neural network which, reached 80% to 90% accuracy in the training and validation session that made the architecture sufficient for determining the growth of the said vegetable. This is indeed foreseen, will highly assist the farmer in better monitoring the growth rate of the plant.
  • Publication
    Electronic Nose Testing for Confined Space Application Utilizes Principal Component Analysis and Support Vector Machine
    ( 2020-12-18)
    Muhammad Aizat Abu Bakar
    ;
    Abu Hassan Abdullah
    ;
    Wan Azani Wan Mustafa
    ;
    Zol Bahri Razali
    ;
    Syahrul Affandi Saidi
    ;
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Aman M.N.S.B.S.
    A confined space has a limited space for entry and exit but it is large enough for workers to enter and perform work inside. It is not designed for continuous occupancy because it can contribute atmospheric hazards accidents that threaten the worker safety and industry progress. In this work, we reported the testing an instrument to assist workers for atmosphere testing during pre-entry. An electronic nose (e-nose) using specific sensor arrays is the integration between hardware and software that able to sense different concentrations of gases in an air sample using pattern recognition techniques. The instrument utilizes multivariate statistical analysis which is Principal Component Analysis (PCA) for discriminate the different concentrations of gases and the Support Vector Machine (SVM) to classify the acquired data from the air sample. The instrument was successfully tested using diesel, gasoline, petrol and thinner. The results show that the instrument able to discriminate an air sample using PCA with total variation for 99.94%, while the classifier success rate for SVM indicates at 98.21% for train performance and 95.83% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space to ensure the safety of workers during work progress in a confined space.
      6  40
  • Publication
    Automotive Mechanical Vehicle Starter
    (IOP Publishing, 2021-12-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Zol Bahri Razali
    ;
    Wan Azani Wan Mustafa
    ;
    Syahrul Affandi Saidi
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Setumin S.
    ;
    Osman M.K.
    ;
    Idris M.
    ;
    Akbar M.F.
    ;
    Muhammad Anas Ahmad Sarbini
    ;
    Nor Syamina Sharifful Mizam
    This research is used to crank start automotive vehicle. There are many different system used in order to start-up vehicles using electric starter, in the time of battery low-power or totally drained. The purpose of this research is to help the driver to get out of this difficulty. Nowadays there are many people that have experienced such a bad moment, where they are stranded at road side due to malfunction starter in their car because of battery problem. Most of the vehicle electric starter failure is because of battery corrosion or battery undercharged. The importance of this research is to solve this problem. Starter is a vital part of the vehicle, without it no automotive vehicles able to operate. These starters will rotate an internal-combustion engine to initiate the engine's operation under its own power. Starters also can be malfunction too due to corroded electrical connections or an undercharged battery. This system can be used to solve this problem. This system used human energy by using mechanical parts in order to produce electrical power. In order to produce electrical current, workforce will be applied by rotating the wheel that already linked by belt and from that rotations will trigger a magnetic force and it will produce an electrical current and supply it into battery. This system is divided into two development; hardware development and software development. The hardware development involved, mechanical device which is used and electrical device such as monitor. For software development, Fritzing is used to construct circuit.
      26  33
  • Publication
    Urban farming growth monitoring system using Artificial Neural Network (ANN) and Internet of Things (IOT)
    (Semarak Ilmu Publishing, 2025-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Muhammad Naufal Mansor
    ;
    Wan Azani Wan Mustafa
    ;
    Ahmad Anas Nagoor Gunny
    As an introduction to this project, the growth-related traits, such as above-ground biomass and leaf area, are critical indicators to characterize the growth of indoor lettuce plants. Currently, non-destructive methods for estimating growth-related traits are subject to limitations in that the methods are susceptible to noise and heavily rely on manually designed features. It is also one of the problem statements in this project. Based on this project the next problem is manual control of nutrients may cause quality issues to the lettuce plant. If the nutrient supply is too much or less, it will disturb the growth of the lettuce plant either the lettuce plant is dead or stunted. This project is about urban farming growth monitoring system using Artificial Neural Network (ANN) and Internet of Things (IoT). In this project, a method for monitoring the growth of indoor lettuce plants was proposed by using digital images and an ANN using Deep Learning Architecture. DLA is mostly developed by the software of MATLAB or Python to insert and run the coding. DLA is mostly used for image detection, pattern recognition, and natural language processing through the graph for Neural Network. Next, the Internet of Things (IoT) is a medium to store images of indoor lettuce plant growth into the Cloud (Google Drive). Furthermore, it takes indoor lettuce plant images as the input, an ANN was trained to learn the relationship between images and the corresponding growth- related traits with other fixed parameters. The pH level parameters were controlled by other fixed parameters to take the images of indoor lettuce plant growth. The parameters used in this project are temperature and humidity. This helps to compare the results of Artificial Neural Network (ANN), widely adopted methods were also used. Concisely, this project is expected to develop the Deep Learning Architecture using an Artificial Neural Network (ANN) with digital images as a robust tool for the monitoring of the growth of indoor lettuce plants every 30 minutes per day. Generally, focused on an urban farming growth monitoring system using Artificial Neural Network (ANN) and the Internet of Things (IoT).
      3  1
  • Publication
    Aquaponic Ecosystem Monitoring with IOT Application
    ( 2023-08-01)
    Muhammad Naufal Mansor
    ;
    Mohd Zamri Hasan
    ;
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Wan Azani Wan Mustafa
    ;
    Syahrul Affandi Saidi
    ;
    Mohd Aminudin Jamlos
    ;
    Noor Anida Abu Talib
    Aquaculture is an agricultural technology that combines aquaculture (fish farming activities) with hydroponic activities (planting crops without soil media) in one circulation. The most important element in aquaculture is the existence of fish, plants, and bacteria. These three elements form a mutually beneficial relationship or symbiotic mutualism. The main purpose of the aquaculture system is to maintain water quality and reduce ammonia levels from the water so that it can be utilized by other organisms. In addition, aquaculture can also save space and can produce two types of human food simultaneously, plants and livestock. Agricultural technology design with Aquaculture also uses the concept of Internet of Things (IoT) as information from sensors and sensors of value generator is accessible through applications installed on smartphones from anywhere with an Internet connection. Development of monitoring of aquaponic ecosystems with IoT systems was developed using a program using micro-controls to control temperature, humidity, pH levels and water pumps. There are some improvements made to this project.
      3  42
  • Publication
    Renewable Energy Driven Exhaust Fan for Use in Laboratory via IOT
    (Institute of Electrical and Electronics Engineers Inc., 2021-01-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Wan Azani Wan Mustafa
    ;
    Akbar M.F.
    ;
    Syahrul Affandi Saidi
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Zol Bahri Razali
    ;
    Osman M.K.
    ;
    Setumin S.
    ;
    Idris M.
    ;
    Mahendran Gunaseakaran
    ;
    Nor Syamina Sharifful Mizam
    This paper discussed on the hardware product of renewable energy driven exhaust fan for use in laboratory via IOT. Ventilation is generally deployed in buildings for maintaining user's safety and health. This renewable energy driven exhaust fan is the most considered system in improving the energy saving while sustaining user's safety and health. If we can renew and reuse the energy we waste, it would help in some way to the problem of scarcity of energy, which is major threat of present world. Initial capital cost of solar systems is still quite high when it comes to generate power for domestic. By using the concept of wind turbines wind-generated electricity can be used for battery charging and for connection with the power grid. Hence this research proposes a prototype of Renewable Energy Driven Exhaust Fan for use in laboratory via IOT. This research presents a prototype of regenerating power by an exhaust fan. The generated power can be either used directly or can be stored in a battery. This exhaust fan also can be controlled and monitored via IOT. The objectives of this research are, to design and develop an exhaust fan that can be driven by renewable energy, to design and develop an exhaust fan that can be controlled by IoT and to collect data and analyze the power consumptions and power saving. Methods used in this research is to use power from battery to operate the Fan 1. Than this kinetic energy produced by Fan 1 is used to drive Fan 2 and Fan 3 which are now actually a pair of generators with the help of charging circuit to directly recharge the battery which at first used to power up Fan 1. Analysis is then carried out to evaluate the theory, which actually agreed to the initial theory as presented
      11  63
  • Publication
    Solar powered multiple output buck converter
    (IOP Publishing Ltd, 2020)
    Muhammad Zaid Aihsan
    ;
    Norhanisa Kimpol
    ;
    Liew Hui Fang
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Wan Azani Wan Mustafa
    ;
    Junaidah Ali Mohd Jobran
    ;
    Mohamed Mydin Hj M.Abdul Kader
    Times have certainly changed over the past few decades, now it seems that technology is getting more compact and efficient. The modern outdoor enthusiast such as hikers, climbers has a problem regarding the lack of power supply to power up electronics when they go for adventure activities. In order to solve this problem, this paper design and develop DC/DC buck converter system to drop down the voltage from the solar photovoltaic (PV) system from 12VDC into 5VDC. This paper is first to start up with design and simulation circuit using simulation to test outcome of this paper in the range of 5VDC & 1.0A and 5VDC & 0.5A. A battery storage is needed to feed electricity independent and battery management of the battery is needed to improve the performance of battery life. This can be done by adding a charge controller unit. The outcome of this paper allows the battery to be charged using the solar panel and at the same time can produce multiple outputs for low voltages used. The software simulation has been done to shows this system produces two different output and the hardware will be developed based on the software results. Software and hardware result, both will be compared and analysed.
      1  18
  • Publication
    Malaria Parasite Diagnosis Using Computational Techniques: A Comprehensive Review
    ( 2021-12-01)
    Wan Azani Wan Mustafa
    ;
    Hiam Alquran
    ;
    Muhammad Zaid Aihsan
    ;
    Mohd Saifizi Saidon
    ;
    Wan Khairunizam Wan Ahmad
    ;
    Aimi Salihah Abdul Nasir
    ;
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Midhat Nabil Ahmad Salimi
    ;
    Mohd Wafi Nasrudin
    Malaria is a very serious disease that caused by the transmitted of parasites through the bites of infected Anopheles mosquito. Malaria death cases can be reduced and prevented through early diagnosis and prompt treatment. A fast and easy-to-use method, with high performance is required to differentiate malaria from non-malarial fevers. Manual examination of blood smears is currently the gold standard, but it is time-consuming, labour-intensive, requires skilled microscopists and the sensitivity of the method depends heavily on the skills of the microscopist. Currently, microscopy-based diagnosis remains the most widely used approach for malaria diagnosis. The development of automated malaria detection techniques is still a field of interest. Automated detection is faster and high accuracy compared to the traditional technique using microscopy. This paper presents an exhaustive review of these studies and suggests a direction for future developments of the malaria detection techniques. This paper analysis of three popular computational approaches which is k-mean clustering, neural network, and morphological approach was presented. Based on overall performance, many research proposed based on the morphological approach in order to detect malaria.
      9  32
  • Publication
    Development of a Multi-Fan System (MFS) in a Plant Factory with Artificial Light
    ( 2022-01-01)
    Mohamed Mydin Hj M.Abdul Kader
    ;
    Zol Bahri Razali
    ;
    Wan Azani Wan Mustafa
    ;
    Muhammad Naufal Mansor
    ;
    Ahmad Anas Nagoor Gunny
    ;
    Akbar M.F.
    ;
    Osman M.K.
    ;
    Setumin S.
    ;
    Idris M.
    ;
    Bin Ramli M.A.
    ;
    Sharifful Mizam N.S.
    A plant factory is a factory that grows plants indoors. These indoor farms could be the key to solve food shortages in the world. Plant factories are operated in indoor spaces under controlled cultivation conditions such as light, temperature and humidity. Then, a multi-fan system (MFS) for single culture beds. The MFS had four fans which were installed on both the front and back sides of culture beds to generate airflow from two opposite horizontal directions by using the Internet of Things (IoT) via the access and connection of smartphone devices. The fans that push the air into the culture bed were air inlets while those that pull the air out of the culture bed were air outlets. The main problem is in plant factories with artificial light, a heat that is usually used to control the environmental parameters and the air velocity is generally lower than the optimum range required for plant growth. Compare to a plant factory without using a multi-fan, it no circulation of air in the container to ensure continuous gas exchange. This reduction in gas exchange can impact calcium uptake by the plants. The gas exchange makes the tip burn. Tip burn can have a significant impact on the salability of a lettuce crop. Based on the limitations that have been highlighted previously, this research has been carried out by using multi-fan and without multi-fan. To get the data that need to be compared. Then, to improve the airflow in a plant factory with artificial light and prevent tip burn occur on the lettuce itself. In a nutshell, this prototype is expected to help plant factories reduce tip burn symptoms on leaf lettuce and the airflow can improve the growth of indoor cultured lettuce.
      2  1
  • Publication
    Solar Powered Multiple Output Buck Converter
    ( 2020-12-18)
    Muhammad Zaid Aihsan
    ;
    Norhanisa Kimpol
    ;
    Liew Hui Fang
    ;
    Muhammad Izuan Fahmi Romli
    ;
    Wan Azani Wan Mustafa
    ;
    Junaidah Ali Mohd Jobran
    ;
    Mohamed Mydin Hj M.Abdul Kader
    Times have certainly changed over the past few decades, now it seems that technology is getting more compact and efficient. The modern outdoor enthusiast such as hikers, climbers has a problem regarding the lack of power supply to power up electronics when they go for adventure activities. In order to solve this problem, this paper design and develop DC/DC buck converter system to drop down the voltage from the solar photovoltaic (PV) system from 12VDC into 5VDC. This paper is first to start up with design and simulation circuit using simulation to test outcome of this paper in the range of 5VDC & 1.0A and 5VDC & 0.5A. A battery storage is needed to feed electricity independent and battery management of the battery is needed to improve the performance of battery life. This can be done by adding a charge controller unit. The outcome of this paper allows the battery to be charged using the solar panel and at the same time can produce multiple outputs for low voltages used. The software simulation has been done to shows this system produces two different output and the hardware will be developed based on the software results. Software and hardware result, both will be compared and analysed.
      46  6